Development and application of the WRFDA-Chem 3DVAR system: aiming to improve air quality forecast and diagnose model deficiencies

Abstract

<p><strong>Abstract.</strong> To improve the operational air quality forecasting over China, a new aerosol/gas phase pollutants assimilation capability is developed within the WRFDA system using 3DVAR algorithm. In this first application, the interface for MOSAIC aerosol scheme is built with flexible extending potentials. Based on the new WRFDA-Chem system, five experiments assimilating different surface observations, including PM<sub>2.5</sub>, PM<sub>10</sub>, SO<sub>2</sub>, NO<sub>2</sub>, O<sub>3</sub>, and CO are conducted for January 2017 along with a control experiment without DA. Results exhibit that the WRFDA-Chem system evidently improves the air quality forecasting. On the analysis aspect, the assimilation of surface observations reduces the bias and RMSE in the initial condition (IC) remarkably; on the forecast aspect, better forecast performances are acquired up to 24-h, in which the experiment assimilating the six pollutants simultaneously displays the best forecast skill overall. With respect to the impact of DA cycling frequency, the responses toward IC updating are found out to be different among the pollutants. For PM<sub>2.5</sub>, PM<sub>10</sub>, SO<sub>2</sub> and CO, the forecast skills increase with the DA frequency; for O<sub>3</sub>, although improvements are acquired at the 6-h cycling frequency, the advantage of more frequent DA could be consumed by the disadvantage of unbalanced photochemistry (due to inaccurate precursor NOx/VOC ratios) from assimilating the existing observations (only O<sub>3</sub> and NO<sub>2</sub>, but no VOC). Considering after one aspect (IC) in the model is corrected by DA, the deficiencies from other aspects (e.g., chemical reactions) could be more evident, this study further explores the model deficiencies by investigating the effects of assimilating gaseous precursors on the forecast of related aerosols. Results exhibit that the parameterization (uptake coefficients) in the newly added Sulfate-Nitrate-Ammonium (SNA) relevant heterogeneous reactions in the model are not fully appropriate although it best simulates observed SNA aerosols without DA; since the uptake coefficients were originally tuned under the inaccurate gaseous precursor scenarios without DA, the biases from the two aspects (SNA reactions and IC DA) were just compensated. In the future chemistry development, parameterizations (such as uptake coefficients) for different gaseous precursor scenarios should be adjusted and verified with the help of DA technique. According to these results, DA ameliorates certain aspects by using observation as constraints, and thus provides an opportunity to identify and diagnose the model deficiencies; it is useful especially when the uncertainties of various aspects are mixed up and the reaction paths are not clearly revealed. In the future, besides being used to improve the forecast through updating IC, DA could be treated as another approach to explore necessary developments in the model.<p>